Role Overview
We are seeking an ML Developer with expertise in natural language processing and financial compliance to design, implement, and benchmark deterministic and transformer-based detection models for electronic communication surveillance. This role is central ability to detect market abuse, conduct risk, information barrier breaches, and off-channel evasion across trader communications.
ASIC INFO 283 explicitly warns against reliance on vendor default alert thresholds, requiring licensees to calibrate models to their specific risk profile. You will build the model benchmarking framework that continuously tests and measures detection model effectiveness, enabling to demonstrate to regulators that its surveillance models are tuned, validated, and performing to measurable standards.

Location open: Bangalore / Gurgaon

Key Responsibilities
Design and implement deterministic detection models for eComms surveillance: market abuse language, insider information patterns, tipping-off phraseology, information barrier breaches, conduct risk, off-channel evasion,



and trade-comms correlation
Develop and fine-tune transformer-based NLP models (BERT, RoBERTa, FinBERT) for context-aware detection beyond straightforward lexicon matching
Build and maintain a model benchmarking framework with ground truth datasets, precision/recall/F1 measurement, AUC-ROC analysis, and automated weekly benchmark runs
Implement threshold tuning workflows to calibrate alert sensitivity per desk, asset class, and jurisdiction — ensuring compliance with ASIC INFO 283 guidance
Design false positive reduction strategies: contextual filtering, trader baseline profiling, alert clustering, and analyst feedback loops
Develop false negative detection: red team simulated misconduct, historical replay testing, coverage gap analysis, and cross-model ensemble voting
Prepare communication data for transformer models: tokenisation, sequence formatting with context windowing, label engineering from investigations, and

📌 Machine Learning Engineer (Bengaluru)
🏢 Accolite
📍 Bengaluru